Karla Badillo-Urquiola

Ozioma C. Oguine, Elmira Rashidi, Pamela J. Wisniewski et al.

Ecological Momentary Assessment (EMA) is widely used to study adolescents' experiences; yet, how the design of EMA platforms shapes engagement, research practices, and power dynamics in youth studies remains under-examined. We developed a youth-centered EMA platform prioritizing youth engagement and researcher support, and evaluated it through a case study on a longitudinal investigation with adolescent twins focused on mental health and sleep behavior. Interviews with the research team examined how the platform design choices shaped participant onboarding, sustained engagement, risk monitoring, and data interpretation. The app's teen-centered design and gamified features sustained teen engagement, while the web portal streamlined administrative oversight through a centralized dashboard. However, technical instability and rigid data structures created significant hurdles, leading to privacy concerns among parents and complicating the researchers' ability to analyze raw usage metadata. We provide actionable interaction design guidelines for developing EMA platforms that prioritize youth agency, ethical practice, and research goals.

Johanna Olesk, Ozioma C. Oguine, Mariana Fernandez Espinosa et al.

Current online safety technologies overly rely on parental mediation and often fail to address the unique challenges faced by youth in the Child Welfare System (CWS). These youth depend on a complex ecosystem of support, including families, caseworkers, and advocates, to safeguard their wellbeing. Within this network, Guardians ad Litem (GALs) play a unique role as court-appointed advocates tasked with ensuring the best interests of youth. Yet little is known about how GALs perceive and support youths' online safety. To address this gap, we conducted a two-part workshop with 10 GALs to explore their perspectives on online safety and collaboratively envision technology-based solutions tailored to the needs of youth in the CWS. Our findings revealed that GALs struggle to support youth with online safety challenges due to limited digital literacy, inconsistency of institutional support, lack of collaboration among stakeholders, and complexity of family dynamics. While GALs recognized the need for some oversight of youth online activities, they emphasized designing systems that support online safety beyond control or restriction by fostering stability, trust, and meaningful interactions, both online and offline. GALs emphasized the importance of developing tools that enable ongoing communication, therapeutic support, and coordination across stakeholders. Proposed design concepts focused on strengthening youth agency and cross-stakeholder collaboration through virtual avatars and mobile apps. This work provides actionable design concepts for strengthening relationships and communication across care network. It also redefines traditional approaches to online safety, advocating for a holistic, multi-stakeholder online safety paradigm for youth in the CWS.

Ruyuan Wan, Simret Gebreegziabhe, Toby Jia-Jun Li et al.

In recent years, there has been a growing interest in employing intelligent agents in writing. Previous work emphasizes the evaluation of the quality of end product-whether it was coherent and polished, overlooking the journey that led to the product, which is an invaluable dimension of the creative process. To understand how to recognize human efforts in co-writing with intelligent writing systems, we adapt Flower and Hayes' cognitive process theory of writing and propose CoCo Matrix, a two-dimensional taxonomy of entropy and information gain, to depict the new human-agent co-writing model. We define four quadrants and situate thirty-four published systems within the taxonomy. Our research found that low entropy and high information gain systems are under-explored, yet offer promising future directions in writing tasks that benefit from the agent's divergent planning and the human's focused translation. CoCo Matrix, not only categorizes different writing systems but also deepens our understanding of the cognitive processes in human-agent co-writing. By analyzing minimal changes in the writing process, CoCo Matrix serves as a proxy for the writer's mental model, allowing writers to reflect on their contributions. This reflection is facilitated through the measured metrics of information gain and entropy, which provide insights irrespective of the writing system used.

Devansh Saxena, Karla Badillo-Urquiola, Pamela Wisniewski et al.

Algorithms have permeated throughout civil government and society, where they are being used to make high-stakes decisions about human lives. In this paper, we first develop a cohesive framework of algorithmic decision-making adapted for the public sector (ADMAPS) that reflects the complex socio-technical interactions between \textit{human discretion}, \textit{bureaucratic processes}, and \textit{algorithmic decision-making} by synthesizing disparate bodies of work in the fields of Human-Computer Interaction (HCI), Science and Technology Studies (STS), and Public Administration (PA). We then applied the ADMAPS framework to conduct a qualitative analysis of an in-depth, eight-month ethnographic case study of the algorithms in daily use within a child-welfare agency that serves approximately 900 families and 1300 children in the mid-western United States. Overall, we found there is a need to focus on strength-based algorithmic outcomes centered in social ecological frameworks. In addition, algorithmic systems need to support existing bureaucratic processes and augment human discretion, rather than replace it. Finally, collective buy-in in algorithmic systems requires trust in the target outcomes at both the practitioner and bureaucratic levels. As a result of our study, we propose guidelines for the design of high-stakes algorithmic decision-making tools in the child-welfare system, and more generally, in the public sector. We empirically validate the theoretically derived ADMAPS framework to demonstrate how it can be useful for systematically making pragmatic decisions about the design of algorithms for the public sector.

Devansh Saxena, Karla Badillo-Urquiola, Pamela J. Wisniewski et al.

The U.S. Child Welfare System (CWS) is charged with improving outcomes for foster youth; yet, they are overburdened and underfunded. To overcome this limitation, several states have turned towards algorithmic decision-making systems to reduce costs and determine better processes for improving CWS outcomes. Using a human-centered algorithmic design approach, we synthesize 50 peer-reviewed publications on computational systems used in CWS to assess how they were being developed, common characteristics of predictors used, as well as the target outcomes. We found that most of the literature has focused on risk assessment models but does not consider theoretical approaches (e.g., child-foster parent matching) nor the perspectives of caseworkers (e.g., case notes). Therefore, future algorithms should strive to be context-aware and theoretically robust by incorporating salient factors identified by past research. We provide the HCI community with research avenues for developing human-centered algorithms that redirect attention towards more equitable outcomes for CWS.